• Define and drive the technical strategy for Cloud Resource management within Ad first, ensuring that cost accountability is built into the architecture of our systems. • High-Fidelity Investment Modeling: Elevate cloud estimation from guesswork to a rigorous engineering discipline. You will lead the high-quality forecasting of new cloud investments and efficiency projects, designing data-driven models to validate technical ROI before builds happen. • Design and implement a roadmap for Cost Observability 2.0, moving beyond simple reporting to real-time, service/team-level spend attribution and automated anomaly detection. • Design and build internal platforms that programmatically enforce PnL accountability. You will engineer (or collaborate with Core Infrastructure partners) to deliver the dashboards, alerts, and governance tools that every Ads team relies on to manage their cloud footprint. • Architect automated frameworks for validating cost estimates and forecasting, replacing manual spreadsheets with data-driven software solutions. • Fight for observability by instrumenting deep telemetry into our cloud infrastructure. You will be hands-on in identifying inefficiencies (e.g., underutilized clusters, uncompressed data flows) and re-architecting critical paths for cost reduction. • Lead the technical validation of vendor and 3rd-party tool integration, ensuring we extract maximum engineering value from every dollar spent. • Act as a role model for the Ads domain and the wider company. You will set the standard for how engineering teams think about Cost as a Non Functional Requirement, eventually scaling these patterns to other domains. • Partner with Finance and Engineering leadership to translate Cloud Spend into actionable engineering tasks (e.g., refactor Service X to use Spot instances).